Mathematics graduate student Aditi Sen's research refines survey analysis when few people respond—with sweeping applications. 

By Jason P. Dinh

Aditi Sen (M.S. ‘25, applied mathematics & statistics, and scientific computation) loves statistics for its ubiquitous nature. 

“I love statistics because it is everywhere—quietly shaping data-driven decisions across every field,” said Sen, who is now a Ph.D. candidate in applied mathematics & statistics, and scientific computation at the University of Maryland. 

Guided by that interest, Sen’s dissertation focuses on how to make the estimates generated from real-world survey data more precise. 

Sen develops new methods to generate more precise survey estimates for small areas, where few or no people respond. Her approaches merge insights from multiple datasets—a technique called statistical data integration. This method leverages the strengths of different sources—for instance, in sample coverage or the types of questions asked—to cover for each one’s weaknesses, yielding more precise estimates with little added cost. 

Sen’s work can be applied to public health interventions and policy design. Governments, for example, rely on surveys to gather localized data to guide how they target their policies, funding and resources. 

“The problem is that when you look at granular levels, like counties or districts, you may not even have data,” Sen said. “That’s where we want to contribute.”

Born to be a statistician

Sen may have always been destined to become a statistician. She grew up in Calcutta, India—the hometown of Prasanta Chandra Mahalanobis, known as the father of Indian Statistics, who introduced a popular statistical metric called Mahalanobis distance. 

Sen earned a bachelor’s degree in statistics from Presidency University in India, followed by a master’s degree at the University of Calcutta. She went on to work as a data analyst for HSBC—Europe’s largest bank by total assets—where she applied her statistical acumen to analyze issues related to banking transactions, personal loans and credit card transactions. 

“Those were some of my very formative years,” Sen said. “But it was always in me to learn more about the subject and improve the methods.” 

So, she enrolled at UMD to pursue her Ph.D. 

From COVID-19 to presidential elections

Working with her advisor, Partha Lahiri, a professor in the Joint Program in Survey Methodology and the Department of Mathematics, Sen quickly took on projects that could benefit the world outside of academia. 

Compared with her prior coursework, “survey statistics is taught at UMD in a very different way,” Sen said. “It focuses on the applications and how it is useful to us.” 

Early in her Ph.D., Sen researched how the American public perceived masking in response to COVID-19. She analyzed data from a coronavirus survey conducted by the University of Southern California. This dataset struggled to generate reliable estimates in smaller states such as Delaware and Wyoming, where only three to four people responded. 

To better grasp public opinion in these areas, Sen integrated insights from multiple large datasets produced by the U.S. Census Bureau. Her approach gleaned valuable information from these massive surveys, even though they didn’t ask specifically about COVID-19. She built a predictive model that characterized the geographic and demographic attributes in each state using the Census data, then fed those characteristics back into the COVID-19 survey. In states with few survey respondents, the new model drew on responses from demographically similar states to improve estimates. The research was published as an editor’s invited paper in the journal Statistics in Transition New Series in 2022. 

Later, Sen used open-access Pew Research Center data to improve U.S. presidential polling data for areas with few or no respondents. Her new method, published in the Journal of Survey Statistics and Methodology in 2025, started by identifying economic and demographic characteristics that predicted presidential preference using Pew’s dataset. Then, similar to the COVID-19 study, the model pulled relevant Census Bureau data to estimate presidential preference based on demographics in districts where few to no people responded. The paper won the student paper competition for the Washington, DC chapter of the American Association for Public Opinion Research in 2024.

“Aditi’s research on COVID-19 masking has given us some really critical insights into how public health actually works on the ground,” Lahiri said. “Beyond that, I’ve been incredibly impressed with her work on election forecasting; by finding ways to combine different data sources to make projections more precise, she’s tackling one of the biggest challenges in modern polling.”

For the promise and impact of her research, Sen won the American Statistical Association’s Edward C. Bryant Scholarship for an Outstanding Graduate Student in Survey Statistics at the Joint Statistical Meetings—the largest gathering of statisticians in North America—in 2025.

“Being named the sole winner of the 2025 Edward C. Bryant Scholarship from the American Statistical Association is a huge deal,” Lahiri added. “It really highlights her technical skill and her ability to apply survey statistics to messy, real-world problems.”

Inside the statistical mind of ChatGPT

Sen’s latest project looks under the hood of transformer models, which are a type of advanced neural network behind the mass proliferation of generative artificial intelligence. Examples of transformer-based models include ChatGPT (the “T” stands for transformer), the image-generation program DALL-E and the Nobel Prize-winning protein-folding software AlphaFold. 

Transformer models can learn rules, context and meaning at scale, but the fundamental statistics that govern them are murky. Because transformer models are, at their core, predictive models like those used in survey analysis, Sen suspects that demystifying their foundations could yield profound insights for her field. 

Sen hopes to continue this work as she seeks postdoctoral and faculty positions, sharpening her skills in statistical learning theory and applying abstract concepts to benefit people outside of academia. 

“If I can make a difference in public health applications, that would be something I would feel good about,” Sen explained. “That's what I love and find really useful about survey statistics—that this work can be applied to benefit any person in any field.”

The workshop participants reflected on 25 years of U.S. Office of Naval Research applied and computational analysis and related programs.

 Participants of the Contemporary Issues and Future Opportunities in Applied Mathematics stand on the steps of the Kirwan Hall math building.
Image Credit: Natalie Kinnear

The Brin Mathematics Research Center hosted a workshop in October 2025 on "Contemporary Issues and Future Opportunities in Applied Mathematics" in honor of Reza Malek-Madani's retirement as director of the U.S. Office of Naval Research's (ONR) Applied and Computational Analysis program.

The workshop was organized by Nam Chen (University of Wisconsin–Madison), Doron Levy and Eitan Tadmor (UMD), and Evelyn Lunasin and Stephen Wiggins (U.S. Naval Academy), and brought together 40 researchers who contributed to ONR activities over the past 25 years to reflect on the lasting impact of the applied and computational analysis and related programs.

The Brin MRC enabled scores of researchers from different disciplines to come together and provide a brief overview of their ONR-supported research. Those attending praised Malek-Madani for his remarkable interdisciplinary vision. Young researchers acknowledged his constructive role in their careers, mid-career researchers highlighted how he was instrumental in fostering connections, and senior researchers lauded his gentle guidance across various domains—from clouds and atmospheric dynamics to weather prediction, from shallow-water and sea ice to oceanography, geophysical processes, stochastic modeling, and a wide range of novel mathematical methodologies for experiments, modeling and simulations.

Washington was recognized for his transformative impact on student success and program innovation during his nearly 50 years at UMD.

Professor Lawrence Washington, a 48-year veteran of the University of Maryland’s Department of Mathematics, has been selected to receive the prestigious 2025-26 Kirwan Undergraduate Education Award at the Faculty & Staff Convocation on September 17, 2025, in the Memorial Chapel.

Washington with Brin Math Camp participants. Credit: Mark Sherwood.

The Kirwan Undergraduate Education Award, established to honor outstanding faculty who demonstrate excellence in undergraduate teaching and educational leadership, recognizes individuals who have made significant contributions to student learning and academic program development. Named after former UMD President and Mathematics Professor Emeritus William “Brit” Kirwan, the award celebrates educators who embody a commitment to undergraduate student success and innovation in teaching practices.

"This award honors Professor Washington's lifelong contributions to the educational mission of our institution. It would not be superlative to state that he has dedicated his life to education," said Doron Levy, chair of UMD's Department of Mathematics. "His impact on the department, on our university and on the community is unparalleled. We are proud that one of our best has been recognized with the Kirwan Undergraduate Award." 

For Washington, the award holds special significance as it’s named after Kirwan—the very person who hired him as a UMD faculty member in 1978.

“It’s very special to me in that way, because I’ve known Kirwan for quite some time now,” Washington said. “It almost feels like things have come full circle.” 

Washington’s journey at UMD began in 1977. He came to the university as a visiting professor specializing in number theory after completing his Ph.D. at Princeton University and serving as an assistant professor at Stanford University. But what started as a temporary position at UMD evolved into a lifelong commitment to mathematics education and student development. 

From his earliest days at Maryland, Washington has been deeply involved in outreach and mentoring. He began as an advisor to the Math Club and made weekly mentoring visits to Montgomery Blair High School’s math team, but soon branched out to create numerous programs that have transformed UMD’s mathematics programs. As the associate chair for undergraduate studies since 2021, Washington spearheaded numerous student-focused initiatives that have shaped math education, from recruitment efforts to curricula development to undergraduate research experiences. He also served as associate chair for graduate studies from 2011 to 2016 and was named a Distinguished Scholar-Teacher in 2011.

Over his nearly 50-year career, Washington’s proudest achievements include the university’s high school math competition, the math department’s credit-by-exam program (which now serves over 500 students annually) and multiple summer programs like the Brin Maryland Mathematics Camp for talented high school students—all programs Washington helped to design.

“I like to think I helped recruit a lot of very excellent students to come here to UMD,” Washington noted. “Maintaining these relationships with local schools cemented UMD as a potential destination for talented scholars and an important part of the community. It’s also been helpful in cultivating a culture of excellence here in our department.”

Washington’s work on designing and improving course curricula also shaped the undergraduate learning experience at UMD. He has been deeply involved in creating specialized courses for students with advanced mathematical backgrounds, including MATH 340-341 (an accelerated sequence that combines multivariable calculus, linear algebra and differential equations) and MATH 456 (a cryptography course). In response to federal and state funding shortfalls, Washington also helped develop a summer program  to help undergraduates gain mathematics research experience to prepare them for graduate school or their chosen careers. 

What further sets Washington apart is his genuine commitment to listening to students and adapting his work to meet their needs. His efforts to understand students and bridge the gap between them and faculty led to practical improvements across the undergraduate math curriculum, including improvements in grading practices and better balances between routine practice questions and expanded learning opportunities. 

“Part of my job is to really talk to students,” Washington said. “My door is open at all times. I talk to as many undergrads as I can and I’ve learned a lot.” 

After 48 years, Washington still embraces new challenges.

“There are so many fields that are emerging and evolving, and math is something that everyone needs to take to proceed to these fields,” Washington said. “For example, we’re currently integrating data science and other quickly growing disciplines into the mathematics curriculum, ensuring that course requirements across the university truly serve students’ needs. To prepare students for success in their chosen paths, we have to work together with other departments across campus.”

With a new semester on the horizon, Washington’s strong commitment to students continues.

“UMD has been my home for 48 years,” Washington said. “When I retire, I’ll just be in the emeritus office instead, and I’ll still be advising and supporting where I can.” 

UMD mathematicians identified vaccination strategies that could completely eliminate HPV-related cancers. 

Cervical cancer is the fourth most common cancer for women in the world, with more than 660,000 new cases and nearly 350,000 deaths per year. Now, University of Maryland mathematicians have developed effective strategies to help contain and potentially eliminate the disease. The research, published last week in the journal Bulletin of Mathematical Biology, offers a new mathematical model that can help public health officials design effective vaccination and cancer screening policies.

Abba Gumel, a Distinguished University Professor of Mathematics and the Michael and Eugenia Brin Endowed E-Nnovate Chair in Mathematics at UMD, who holds joint appointments in the Institute for Health Computing and the Institute for Physical Science and Technology. Credit: Mark Sherwood

“The study provides a clear way of showing how science is influencing policy,” said study senior author Abba Gumel, a Distinguished University Professor of Mathematics at UMD who holds joint appointments in the Institute for Health Computing and the Institute for Physical Science and Technology. 

Nearly all cervical cancer cases are caused by human papillomavirus (HPV), which is considered the most common sexually transmitted infection in the world. HPV, a vaccine-preventable disease, is often asymptomatic and resolves naturally within two years in 90% of cases, but persistent infection in the remainder can lead to cancer.

HPV vaccines, which are already offered and recommended in 147 countries, can minimize disease spread and cancer risk. The UMD researchers developed a new mathematical model to assess the efficacy of various vaccination strategies, which they tested with a case study on South Korea. 

“Cervical cancer is one of the few cancers effectively prevented by vaccines,” said study lead author Soyoung Park, a Ph.D. candidate in applied mathematics & statistics, and scientific computation at UMD. “It was important to check if the recent government program for offering vaccines is going to be enough to effectively control the disease in Korea.”

Building a case study for South Korea

The model presented in the study incorporates previously published demographic and epidemiological data to predict how HPV transmits across a population. It stratifies people by sex, vaccination status, HPV infection and cancer progression, and it was calibrated using South Korean cancer data from 1999 to 2020. The model can be used to test how different vaccination strategies fare over time.

Simulations of the model revealed that current South Korean policies are insufficient to eliminate HPV and related cancers in the country. South Korea’s National Immunization Program (NIP), which started in 2016, currently vaccinates roughly 80% of the nation’s girls aged 12-17. Another 30,000 women aged 18-26 receive “catch-up vaccinations” annually. Additionally, the National Cancer Screening Program provides regular Pap tests to detect cancerous lesions for roughly 61% of Korean women older than 20. These existing efforts will reduce HPV-associated cancer burden over time, the authors found, but they will not eliminate the virus. 

“It’s achieving the objective of reducing cases of cervical cancer, but it’s not going to eliminate it,” said Gumel, who has collaborated with the modeling team of Merck Inc., the company that originally developed the HPV vaccine. “The objective is elimination.” 

South Korea could eliminate HPV by expanding vaccine access, the researchers found. The authors explored two scenarios where NIP could be improved. The first involved expanding vaccine access to cover 99% of females. Additionally, because the authors found that immunizing boys has a strong spillover effect of protecting females, the second scenario involved maintaining the current 80% female vaccination coverage while vaccinating 65% of boys aged 12-17. Model simulations suggest that these efforts would eliminate HPV-related cancers in South Korea within 60 and 70 years, respectively. 

Both vaccination strategies for expanded coverage are feasible in Korea given that national coverage for infant immunizations, such as measles, under NIP approaches 98%, Park said. She added that public buy-in for vaccination campaigns is high in South Korea. 

“There’s very low vaccine hesitancy,” she said. 

“Vaccinating boys reduces the pressure of having to vaccinate a large proportion of females,” added Gumel, who also holds the Michael and Eugenia Brin Endowed E-Nnovate Chair in Mathematics. “It makes elimination more realistically achievable.”

Applying the model around the world

The two solutions the researchers propose would achieve herd immunity, meaning that people who cannot be vaccinated—for example, the elderly or those allergic to the vaccine—would be protected against HPV and related cancers. 

“The way to protect them is to surround them with a sea of immunity,” Gumel said. 

The authors showed that while expanding Pap test coverage may only offer marginal benefits, strategies that promote safer sex practices, like condom use, would be very effective in curtailing the burden of HPV and related cancers in communities. 

Now, Park is tweaking the model to explicitly account for the contact dynamics of men who have sex with men, as well as other high-risk groups, such as female sex workers. 

At a conference talk last year in South Korea, Park connected with researchers who work closely with Korean public health agencies. They showed strong interest in sharing data and potentially using the study to improve NIP. She added that the findings are applicable around the world—including in the U.S. 

“We could use different data to compare the lessons learned about HPV to the U.S.,” Park said. “Can we do the same thing? Will the same set of intervention strategies work effectively here?” 

Gumel sees reason to try. He reckons that with the 95% effective Gardisil-9 vaccine offered in the U.S., around 70% coverage would be sufficient to achieve herd immunity.

“We do not have to be losing 350,000 people globally to cervical cancer each year,” Gumel said. “We can see an end to HPV and HPV-related cancers if we improve the vaccination coverage.”

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UMD mathematics Ph.D. candidate Hyunah Lim co-authored this article with Gumel and Park.

The paper, “Mathematical Assessment of the Roles of Vaccination and Pap Screening on the Burden of HPV and Related Cancers in Korea,” was published in Bulletin of Mathematical Biology on December 3, 2025.

This research was supported by the U.S. National Science Foundation. This article does not necessarily reflect the views of this organization.